Performance and Energy Analysis of Nighttime Satellite Image Archive Processing Module

The main goal of this work is to analyze the behavior of a nighttime image processing module and find out basic estimates of required computational time and energy consumption for processing large data archives. As part of this work, we have performed the code refactoring of the most computing-intensive module in a system for detecting fishing boat lights. The algorithm is capable of detecting isolated bright spikes that are sharply visible on the sea surface at night. The refactored module has been optimized for effective usage of multi- and many-core Intel Xeon architectures. In the paper, we describe the algorithmic complexity for all computational stages of the module. Also, we have collected detailed statistic data for two data sets, different input parameter sets, and three test beds: Intel (R) Xeon (R) E5-2697A (codename Broadwell), Intel (R) Xeon (R) Gold 6148 (Skylake), and Intel (R) Xeon Phi (R) 7250 (KNL). Key correlations between module behavior and energy consumption are also included in the paper. The results of the study were used for calculations of the estimate time and energy requirements for a whole year archive of day/night band (DNB) images from the Visible Infrared Imaging Radiometer Suite (VIIRS). Moreover, driving factors, including price and legacy software systems, are presented for discussion.